Globally, the prevalence of gastritis is near 50%, which was shown from 40.7% to 56.0% and included 20–30% chronic atrophic gastritis.
H. pylori-negative gastritis was from 17.7% to 20.5%, in which chronic gastritis accounted for 10–15%
[18][19][20]. It indicates that
H. pylori infection is generally consistent with the prevalence of gastritis and
H. pylori-positive gastritis generally accounts for more than 80%. Therefore, it is the basis of clinical application of gastritis in Kyoto classification, as only a small proportion of gastritis may not be infected by
H. pylori. Endoscopic findings of conventional white light imaging (WLI) can initially predict the status of
H. pylori and the suspicious infection according to gastritis in Kyoto classification, and then biopsies are taken according to Sydney system
[3][21]. Kyoto classification of gastritis including diffuse redness, regular arrangement of collecting venules (RAC), fundic gland polyp (FGP), atrophy, xanthoma, hyperplastic polyp, map-like redness, intestinal metaplasia, nodularity, mucosal swelling, white and flat elevated lesion, sticky mucus, depressive erosion, raised erosion, red streak, and enlarged folds. Regarding validation research, RAC, FGP, and red streak were demonstrated with satisfactory diagnostic odds ratios (DOR) for predicting uninfected status. Nodularity, diffuse redness, mucosal swelling, enlarged fold and sticky mucus were significantly associated with current infection. Map-like redness was responsible for past infection, and the overall diagnostic accuracy rate of Kyoto classification of gastritis was more than 80%
[22][23][24][25]. Furthermore, with regard of uninfected status, one study showed RAC had excellent negative predictive value (NPV) of about 90% and sensitivity value of up to 85%
[26]. A meta-analysis including 4070 patients also showed RAC was a valuable endoscopic feature of uninfected status with 0.80 sensitivity, 0.97 specificity, and 0.97 area under the curve (AUC)
[27]. With regard of current infection, Kyoto classification score (including atrophy, IM, enlarged folds, nodularity, and diffuse redness) ≥2 could predict
H. pylori infection with 89.7% accuracy, 78.3% sensitivity, and 92.0% specificity in patients with a high-negative titer of anti-
H. pylori antibody
[28]. One study showed an AUC for
H. pylori infection of WLI was 0.81 in the corpus and 0.71 in the antrum and indigo carmine contrast (IC) method was useful in gastric swelling areas
[29]. Other research reported 0.82–0.92 AUC used self-assembled score systems to predict
H. pylori infection
[30][31]. However, there are two problems that cannot be ignored in real time clinical practice. The first one is the professional level and experience, as well as interobserver agreement. A brief mini-lecture on the Kyoto Classification of Gastritis could improve the accuracy from 90.3% to 96.5%
[32]. The second one is the clinical routine that biopsy rather than other detecting methods (UBT, Hp SAT, or serological test) will be taken after primary prediction via Kyoto Classification of Gastritis. From the data mentioned above, Kyoto Classification of Gastritis is more characterized with higher specificity and slightly inferior sensitivity. One clinical research reported no endoscopic features (alone or in combination) showed a sensitivity of more than 57% for
H. pylori infection
[33], which may further result in increasing missed diagnosis rate. The uneven distribution of
H. pylori inevitably leads to sampling errors in biopsy-based examinations including rapid urease test (RUT), histology, or culture. Biopsies from multipoints can improve the accuracy of detection. Two samples (one from the antrum avoiding areas of ulceration and obvious IM and one from normal appearing corpus) can provide the highest yield for RUT, as well as time saving
[34]. The sensitivity of RUT was reported to vary between 80% and 100%, and its specificity is between 97% and 99%
[35]. If less than 10
4 bacterial cells are present in the gastric biopsy, false-negative results are obtained most probably
[36]. It is essential to improve the sensitivity. Therefore, many efforts were done on newer imaging techniques such as image-enhanced endoscopy (IEE) and aiding systems such as AI.